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Nested Partitioning for the Minimum Energy Broadcast Problem

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Learning and Intelligent Optimization (LION 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5313))

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Abstract

The problem of finding the broadcast scheme with minimum power consumption in a wireless ad-hoc network is NP-hard. This work presents a new hybrid algorithm to solve this problem by combining Nested Partitioning with Local Search and Linear Programming. The algorithm is benchmarked by solving instances with 20 and 50 nodes where results are compared to either optimum or best results found by an IP solver. In these instances, the proposed algorithm was able to find optimal and near optimal solutions.

Work was done while visiting the Distributed Algorithms Group at the University of Kaiserslautern.

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Author information

Authors and Affiliations

  1. Industrial Engineering Department, University of Jordan, Amman, 11942, Jordan

    Sameh Al-Shihabi

  2. Distributed Algorithms Group, University of Kaiserslautern, Germany

    Peter Merz & Steffen Wolf

Authors
  1. Sameh Al-Shihabi
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  2. Peter Merz
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  3. Steffen Wolf
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Editor information

Editors and Affiliations

  1. Dept. Computer Science, University of Bologna, Bologna, Italy

    Vittorio Maniezzo

  2. Università degli Studi di Trento, Trento, Italy

    Roberto Battiti

  3. Discrete Math and Complex Systems Department, Sandia National Laboratories, Albuquerque, New Mexico, USA

    Jean-Paul Watson

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© 2008 Springer-Verlag Berlin Heidelberg

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Al-Shihabi, S., Merz, P., Wolf, S. (2008). Nested Partitioning for the Minimum Energy Broadcast Problem . In: Maniezzo, V., Battiti, R., Watson, JP. (eds) Learning and Intelligent Optimization. LION 2007. Lecture Notes in Computer Science, vol 5313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92695-5_1

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  • DOI: https://doi.org/10.1007/978-3-540-92695-5_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92694-8

  • Online ISBN: 978-3-540-92695-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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